Getting Started

This page is the shortest path: install pg_exporter, connect it to a PostgreSQL instance, verify metrics output, and hook it into Prometheus.

You only need two things: a reachable PostgreSQL 10-19+ (or pgBouncer 1.8+) instance, and permission to create a user in it. For older PostgreSQL 9.1-9.6 instances, see Compatibility.

Step 1: Install

On Linux amd64 you can download the binary directly (for other platforms and RPM/DEB/Docker options, see the Installation guide):

VERSION=$(curl -fsSL https://api.github.com/repos/pgsty/pg_exporter/releases/latest | sed -n 's/.*"tag_name": "v\([^"]*\)".*/\1/p')
wget "https://github.com/pgsty/pg_exporter/releases/download/v${VERSION}/pg_exporter-${VERSION}.linux-amd64.tar.gz"
mkdir -p "pg_exporter-${VERSION}.linux-amd64"
tar -xf "pg_exporter-${VERSION}.linux-amd64.tar.gz" -C "pg_exporter-${VERSION}.linux-amd64"
sudo install "pg_exporter-${VERSION}.linux-amd64/pg_exporter" /usr/bin/
sudo install "pg_exporter-${VERSION}.linux-amd64/pg_exporter.yml" /etc/pg_exporter.yml

Confirm the installation:

pg_exporter --version
# pg_exporter v1.4.1 (built with go1.26.5 on linux/amd64)

Step 2: Create a Monitoring User

Create a dedicated monitoring user on the target PostgreSQL. The built-in pg_monitor role (PostgreSQL 10+) covers all read permissions the default collectors need:

CREATE USER monitor WITH PASSWORD 'S3cret';
GRANT pg_monitor TO monitor;

If you are just trying it out locally as a superuser like postgres, you can skip this step.

Step 3: Run and Verify

Use --dry-run to confirm the configuration parses, then start for real:

export PG_EXPORTER_URL='postgres://monitor:S3cret@localhost:5432/postgres'

pg_exporter --dry-run     # print parsed collector config, then exit
pg_exporter               # start for real, listening on :9630 by default

Without any URL, pg_exporter falls back to the local-first default postgresql:///?sslmode=disable, which fits running on the same host as PostgreSQL. The full URL source precedence (--url > PG_EXPORTER_URL > PGURL > PG_EXPORTER_URL_FILE > default) is documented in the Deployment guide.

Pull the metrics from another terminal:

curl -s http://localhost:9630/metrics | grep -E '^pg_(up|version|in_recovery) '

You should see the three core built-in metrics:

pg_up 1              # 1 when the target is reachable, 0 otherwise
pg_version 170000    # version in server_version_num format
pg_in_recovery 0     # 1 on replicas, 0 on primaries

pg_up 1 means the pipeline works — the remaining 600+ metrics (pg_db_*, pg_table_*, pg_wal_*, …) all come from the declarative collector definitions in pg_exporter.yml. If pg_up is 0, restart with pg_exporter --log.level=debug and inspect the connection error.

Step 4: Hook into Prometheus

Add a scrape target in prometheus.yml:

scrape_configs:
  - job_name: 'postgresql'
    scrape_interval: 15s
    static_configs:
      - targets: ['localhost:9630']

Collectors cache results per their ttl (most realtime collectors use ttl: 10): as long as the TTL is below the scrape interval, every scrape gets fresh data, while high-frequency scraping can never overwhelm the database. This is also why setting scrape_interval below the common TTLs is not recommended.

That’s it. For Grafana, you can reuse the PostgreSQL dashboards from Pigsty, or explore the live demo.

Troubleshooting

/stat, /explain, and /reload are management endpoints — protect them with --web.config.file (TLS/auth) or keep them on a trusted network in production. See the API Reference.

Next Steps

• Monitor pgBouncer, enable auto-discovery, deploy with systemd / Docker / Kubernetes: Deployment guide
• Understand and customize collectors (GAUGE/COUNTER/HISTOGRAM, TTL, tags, version gates): Configuration reference
• Health check and primary/replica traffic routing endpoints (/up, /primary, /replica): API Reference